Effect Of Redundancy Research Articles

Enhancing Laser-Induced Breakdown Spectroscopy Spectral Quantification Through Minimum Redundancy and Maximum Relevance-Based Feature Selection

Laser-induced breakdown spectroscopy (LIBS) is a rapid, non-contact analytical technique that is widely applied in various fields. However, the high dimensionality and information redundancy of LIBS spectral data present challenges for effective model development. This study aims to assess the effectiveness of the minimum redundancy and maximum relevance (mRMR) method for feature selection in LIBS spectral data and to explore its adaptability across different predictive modeling approaches. Using the ChemCam LIBS dataset, we constructed predictive models with four quantitative methods: random forest (RF), support vector regression (SVR), back propagation neural network (BPNN), and partial least squares regression (PLSR). We compared the performance of mRMR-based feature selection with that of full-spectrum data and three other feature selection methods: competitive adaptive re-weighted sampling (CARS), Regressional ReliefF (RReliefF), and neighborhood component analysis (NCA). Our results demonstrate that the mRMR method significantly reduces the number of selected features while improving model performance. This study validates the effectiveness of the mRMR algorithm for LIBS feature extraction and highlights the potential of feature selection techniques to enhance predictive accuracy. The findings provide a valuable strategy for feature selection in LIBS data analysis and offer significant implications for the practical application of LIBS in predicting elemental content in geological samples.

The Effectiveness of Unimodal and Multimodal Warnings on Drivers’ Response Time: A Meta-Analysis

Driving warning systems are of great help in notifying emergencies. Based on the results of former studies as well as the multisensory integration effect (MIE), the current meta-analysis investigated the effectiveness of utilizing unimodal (i.e., auditory, visual, and tactile) and multimodal (i.e., bimodal and trimodal) driving warning systems in drivers’ response time. Sixty eligible articles representing 308 individual studies were included in this meta-analysis. The results showed: First, both auditory warnings (pooled Hedges’ g = 0.98, 95% CI: 0.34 to 1.61, p < 0.01) and tactile warnings (pooled Hedges’ g = 0.77, 95% CI: 0.22 to 1.32, p < 0.01) were found to reduce the response time significantly compared to no warning, but visual warnings did not produce significant benefit; Second, tactile warnings outperformed the visual warnings (pooled Hedges’ g = 0.74, 95% CI: 0.11 to 1.37, p < 0.05); Third, auditory-tactile bimodal warnings surpassed unimodal warnings (p < 0.05); Fourth, drivers’ response time under trimodal warning conditions were shorter than that under bimodal warning conditions but not in a significant level. Overall, the results support multisensory redundant signal effect hypothesis in multimodal conditions. Current study provides a quantitative understanding of the effectiveness of driving warnings and could contribute to the design of related technologies.

Changing vistas of psychosis and antipsychotic drug dosing toward personalized management of antipsychotics in clinical practice.

To discuss current evidence on tapering antipsychotic drugs in view of changing vistas of psychosis, suggesting a provisional framework for safely tapering antipsychotic drugs to an optimal low dose, in collaboration with patients and their relatives, to promote functional recovery while preventing relapse. Paradigm shifts during recent years regarding the nature of psychotic disorders and the role of the dopamine system are discussed, including the positive effects of dopamine blockade in acute psychosis and the limitations and drawbacks of dopamine blockade regarding negative and cognitive symptoms after remission of positive symptoms. Recent advances in tapering strategies and upcoming ways to solve the dilemma between the need to prevent relapses with antipsychotics on the one hand and the need to minimize side effects by tapering these drugs on the other are presented. Modern tapering strategies appear to reduce relapse risk to acceptable levels and offer a feasible personalized option to find the least effective dose to treat and prevent positive symptoms without redundant side effects and functional incapacity. These findings need replication, and several trials that might provide more certainty are on their way. Preliminary evidence and clinical experience indicate that personalized dose reduction of antipsychotics is feasible and safe if carried out in close collaboration with patients and their relatives, according to a provisionally suggested framework presented here. These preliminary directions still must be confirmed, revised, and adjusted according to upcoming trial results. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Normative or Confirmative: Effects of Information Quality and Redundancy in Decision Support Systems.

The study investigates users' tendency to access decision support (DS) systems as a function of the correlation between the DS information and the information users already have, the ongoing interaction with such systems, and the effect of correlated information on subjective trust. Previous research has shown inconclusive findings regarding whether people prefer information that correlates with information they already have. Some studies conclude that individuals recognize the value of noncorrelated information, given its unique content, while others suggest that users favor correlated information as it aligns with existing evidence. The impact of the level of correlation on performance, subjective trust, and the decision to use DS remains unclear. In an experiment (N = 481), participants made classification decisions based on available information. They could also purchase additional DS with different degrees of correlation with the available information. Participants tended to purchase information more often when the DS was not correlated with the available information. Correlated information reduced performance, and the effect of correlation on subjective trust and performance depended on DS sensitivity. Additional information may not improve performance when it is correlated with available information (i.e., it is redundant). Hence, the benefits of additional information and DS depend on the information the system and the operator use. It is essential to analyze the correlations between information sources and design the available information to allow optimal task performance and possibly minimize redundancy (e.g., by locating sensors in different positions to capture independent data).

RNA N6-Methyladenosine-Binding Protein YTHDFs Redundantly Attenuate Cancer Immunity by Downregulating IFN-γ Signaling in Gastric Cancer.

Immunotherapy holds potential as a treatment for gastric cancer (GC), though immune checkpoint inhibitor (ICI) resistance remains an obstacle. One resistance mechanism involves defects in interferon-γ (IFN-γ) signaling, in which IFN-γ is linked to improved responsiveness to ICIs. Herein, the roles of RNA N6-methyladenosine (m6A) modifications in regulation of IFN-γ signaling and the responsiveness to ICIs are unveiled. The m6A-binding protein YTH N6-methyladenosine RNA-binding protein F1 (YTHDF1) is overexpressed in GC tissues, correlating with the suppression of cancer immunity and poorer survival rates. YTHDF1 overexpression impaired the responsiveness to IFN-γ in GC cells, and knockdown studies indicated the redundant effects of YTHDF2 and YTHDF3 with YTHDF1 in IFN-γ responsiveness. RNA immunoprecipitation sequencing revealed YTHDFs directly target interferon regulatory factor 1 (IRF1) mRNA, a master regulator of IFN-γ signaling, leading to reduced RNA stability and consequent downregulation of IFN-γ signaling. Furthermore, in mouse syngeneic tumor models, Ythdf1 depletion in cancer cells resulted in reduced tumor growth and increased tumor-infiltrating lymphocytes, which are attributed to the augmentation of IFN-γ signaling. Collectively, these findings highlight how YTHDFs modulate cancer immunity by influencing IFN-γ signaling through IRF1 regulation, suggesting their viability as therapeutic targets in cancer immunotherapy.

A p-ary Choquet-based multicriteria decision-making model for customer-oriented product design scheme selection

As an efficient customer-oriented product design tool for converting customer requirements (CRs) into quality characteristics (QCs) of a product, quality function deployment (QFD) is applied to the selection of new product design schemes. However, the effective implementation of QFD is hampered by two fundamental challenges: (a) biases in people’s understanding of customer satisfaction and (b) the ambiguously assessed relationship between CRs and QCs because of the inherent uncertainty in human judgment. Therefore, this paper provides a p-ary Choquet-based multicriteria decision-making model to rank new product design schemes considering customer psychological and risk attitudes. The selection of a new product design scheme is divided into two stages. In the first stage, the p-ary Choquet integral converts the objective technical parameters of a new product design scheme into utility, which is the subjective feeling from the perspective of two-factor theory. Then, the integration of 2-additive measures and the Choquet integral is used to account for the redundancy and complementary effects among customer requirements. Finally, a case study of an electric vehicle manufacturing company and a comparison analysis are presented to illustrate the validity of our proposal. The p-ary Choquet-based multicriteria decision-making model realizes customer-oriented product design scheme selection by systematically analyzing customer preferences and bridging the gap between products that are emotionally recognized by customers and those that exhibit excellent performance in terms of functionality and cost.

Effects of blinded and nonblinded sequential human redundancy on inspection effort and inspection outcome in low prevalence visual search

Human redundancy is often used in safety–critical domains to help protect against errors. For example, mammograms are read by two radiologists, or the dose of a drug is calculated by two physicians who perform the task redundantly one after the other. However, the expected reliability gain may be compromised by social loafing (SL), i.e., a reduction of individual effort caused by the team setting. In two laboratory studies, we therefore investigated whether different forms of human redundancy cause SL and impact task outcome. In each experiment, about 20 participants inspected images alone for rare targets, while 40 participants worked in teams of two, either performing the first or second inspection. We measured effort using inspection time and inspection area, and measured task outcome using the number of detected targets and false alarms. While there was no transfer of target marks in experiment 1 (blinded redundancy), the second inspectors in experiment 2 saw marks set during the first inspection (nonblinded redundancy). In experiment 1, data revealed no indications of SL but increased time, area covered, detections and false alarms for team-based relative to solo performance. In experiment 2, teams clearly adapted their inspection intensity. The second inspectors searched the images significantly shorter than the first inspectors. While detected targets did not differ between the two redundant groups, the second inspectors were found to produce significantly fewer false alarms than the first inspectors. However, the advantage of detected targets and area coverage still favored the teams. Thus, the principle of redundancy was effective in both forms of sequential redundancy, even if it led to different behaviors and perceptions at the individual level.

Unifying approaches to understanding capacity in change detection.

To navigate changes within a highly dynamic and complex environment, it is crucial to compare current visual representations of a scene to previously formed representations stored in memory. This process of mental comparison requires integrating information from multiple sources to inform decisions about changes within the environment. In the present article, we combine a novel systems factorial technology change detection task (Blunden et al., 2022) with a set size manipulation. Participants were required to detect 0, 1, or 2 changes of low and high detectability between a memory and probe array of 1-4 spatially separated luminance discs. Analyses using systems factorial technology indicated that the processing architecture was consistent across set sizes but that capacity was always limited and decreased as the number of distractors increased. We developed a novel model of change detection based on the statistical principles of basic sampling theory (Palmer, 1990; Sewell et al., 2014). The sample size model, instantiated parametrically, predicts the architecture and capacity results a priori and quantitatively accounted for several key results observed in the data: (a) increasing set size acted to decrease sensitivity (d') in proportion to the square root of the number of items in the display; (b) the effect of redundancy benefited performance by a factor of the square root of the number of changes; and (c) the effect of change detectability was separable and independent of the sample size costs and redundancy benefits. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Local adaptation can cause both peaks and troughs in nucleotide diversity within populations.

The amount of standing variation present within populations is a fundamental quantity of interest in population genetics, commonly represented by calculating the average number of differences between pairs of nucleotide sequences (nucleotide diversity, π). It is well understood that both background and positive selection can cause reductions in nucleotide diversity, but less clear how local adaptation affects it. Depending on the assumptions and parameters, some theoretical studies have emphasized how local adaptation can reduce nucleotide diversity, while others have shown that it can increase it. Here, we explore how local adaptation shapes genome-wide patterns in within-population nucleotide diversity, extending previous work to study the effects of polygenic adaptation, genotypic redundancy, and population structure. We show that local adaptation produces two very different patterns depending on the relative strengths of migration and selection, either markedly decreasing or increasing within-population diversity at linked sites at equilibrium. At low migration, regions of depleted diversity can extend large distances from the causal locus, with substantially more diversity eroded than expected with background selection. With higher migration, peaks occur over much smaller genomic distances but with much larger magnitude changes in diversity. Across spatially extended environmental gradients, both patterns can be found within a single species, with increases in diversity at the center of the range and decreases towards the periphery. Our results demonstrate that there is no universal diagnostic signature of local adaptation based on within-population nucleotide diversity, so it will not be broadly useful for explaining increased FST. However, given that neither background nor positive selection inflate diversity, when peaks are found they suggest local adaptation may be acting on a causal allele in the region.

Redundant target effects reveal capacity limits for recognizing words as a function of visual field position

Redundant target effects reveal capacity limits for recognizing words as a function of visual field position

Different voice part perceptions in polyphonic and homophonic musical textures

Separate voice part perception has been shown in polyphonic music. However, it remains unclear whether this segregation of voice parts is specific to polyphony or also occurs in homophonic music. This study compared voice part perceptions in polyphony and homophony using a redundant signals effect (RSE) paradigm. The RSE means that reaction times are shorter for two simultaneously presented signals than for one of these signals. At the final position of the four-voice homophonic and polyphonic sequences, notes in two voice parts were altered to out-of-key notes independently or simultaneously. Participants ( N = 208) responded to any deviant tones while withholding responses to non-deviant tones. All combinations of deviant voice parts (i.e., soprano–bass, tenor–bass, and alto–tenor) elicited RSEs in polyphonic and homophonic sequences, suggesting separate voice part perception, irrespective of musical texture. However, evidence of the coactivation of separate perceptual modules was obtained only for polyphonic sequences. Deviants in higher voice parts were detected faster and more accurately than those in lower voice parts in both musical textures. These results indicate that voice parts are perceived separately, with a bias toward higher voice parts in both musical textures, but voice parts are more segregated in polyphony.

The More, the Better? Exploring the Effects of Modal and Codal Redundancy on Learning and Cognitive Load: An Experimental Study

This study explores how receiving identical information from different sources affects learning and cognitive load, focusing on two types of redundancy: modal redundancy, where redundant information comes from two visual sources (images and written text), and codal redundancy, where redundant information comes from two sources of different modalities which utilize the same symbol system (spoken and written text). Using a 2 × 2 between-subjects design involving modal (yes/no) and codal (yes/no) redundancy, 158 participants completed twenty learning tasks, consisting of ten construction and ten recall tasks. Additionally, they rated their cognitive load by indicating their perceived task difficulty and mental load. Overall, results indicate positive main effects of modal redundancy and negative effects of codal redundancy on learning and cognitive load. Furthermore, significant interaction effects suggest that modal redundancy may counterbalance the negative effects of codal redundancy, implying a compensatory mechanism in cognitive processing for construction tasks. These results highlight the importance of considering both modal and codal redundancy and their interaction in instructional design.

Audiovisual integration and sensory dominance effects in older adults with subjective cognitive decline: Enhanced redundant effects and stronger fusion illusion susceptibility.

Subjective cognitive decline (SCD) refers to individuals' perceived decline in memory and/or other cognitive abilities relative to their previous level of performance. Sensory decline is one of the main manifestations of decline in older adults with SCD. The efficient integration of visual and auditory information, known as audiovisual integration, is a crucial perceptual process. This study aims to evaluate audiovisual integration in older adults with SCD. We adopted the audiovisual detection task, the Colavita task, and the Sound-Induced Flash Illusion (SIFI) task to evaluate the audiovisual integration by examining both redundant and illusory effects. Older adults diagnosed with SCD (N=50, mean age=67.8 years) and a control group of non-SCD older adults (N=51, mean age=66.5 years) were recruited. All participants took part in the three aforementioned experiments. The outcomes showed that a redundant effect occurred in both SCD and non-SCD older adults, with SCD older adults gaining more benefits in audiovisual detection task. Moreover, an equivalent amount of the visual dominance effect was observed among both SCD and non-SCD older adults in Colavita task. In addition, older adults with SCD perceived an equal fission illusion but a bigger fusion illusion compared with non-SCD older adults in SIFI task. Overall, older adults with SCD exhibit increased audiovisual redundant effects and stronger fusion illusion susceptibility compared to non-SCD older adults. Besides, visual dominance was observed in both groups via the Colavita task, with no significant difference between non-SCD and SCD older adults. These findings implied that audiovisual integration might offer a potential way for the identification of SCD.

Functional redundancy of the three insulin receptors of cockroaches

Gene duplication is a fundamental evolutionary process which provides opportunities to acquire new gene functions. In the case of the insulin receptors (InRs) in cockroaches and close-related insects, two successive duplications determined the occurrence of three InR genes: InR2, InR1 and InR3, the last two forming a sister cluster to InR2. The biological role of each of the gene duplicates and whether they resulted from neofunctionalization or subfunctionalization is still unclear. The analysis of the sequences from different lineages did not detect positive selection as driving the divergence of InR1 and InR3, discarding neofunctionalization, and suggesting that there is no functional divergence between both gene copies. Using the cockroach Blattella germanica as a model, we have determined that BgInR2 is the gene with the highest expression levels in all the tissues analyzed, both in adult females and males, as well as in nymphs and embryos. BgInR3 is second in expression levels while BgInR1 is expressed at lower levels and only in some tissues. The selective depletion by RNAi of each of the three InRs, analyzed in terms of phenotype and fat body transcriptomic profiles, resulted in essentially redundant effects, with a magnitude approximately proportional to the level of expression of the respective InR. Therefore, the results indicate that the InR duplicates likely experienced a subfunctionalization process, by which the three InRs maintained similar functions but contributing to those functions proportionally to their expression levels.

Multidimensional regularity processing in music: an examination using redundant signals effect.

Music is based on various regularities, ranging from the repetition of physical sounds to theoretically organized harmony and counterpoint. How are multidimensional regularities processed when we listen to music? The present study focuses on the redundant signals effect (RSE) as a novel approach to untangling the relationship between these regularities in music. The RSE refers to the occurrence of a shorter reaction time (RT) when two or three signals are presented simultaneously than when only one of these signals is presented, and provides evidence that these signals are processed concurrently. In two experiments, chords that deviated from tonal (harmonic) and acoustic (intensity and timbre) regularities were presented occasionally in the final position of short chord sequences. The participants were asked to detect all deviant chords while withholding their responses to non-deviant chords (i.e., the Go/NoGo task). RSEs were observed in all double- and triple-deviant combinations, reflecting processing of multidimensional regularities. Further analyses suggested evidence of coactivation by separate perceptual modules in the combination of tonal and acoustic deviants, but not in the combination of two acoustic deviants. These results imply that tonal and acoustic regularities are different enough to be processed as two discrete pieces of information. Examining the underlying process of RSE may elucidate the relationship between multidimensional regularity processing in music.

Homogeneous Ensemble Feature Selection for Mass Spectrometry Data Prediction in Cancer Studies

The identification of important proteins is critical for the medical diagnosis and prognosis of common diseases. Diverse sets of computational tools have been developed for omics data reduction and protein selection. However, standard statistical models with single-feature selection involve the multi-testing burden of low power with limited available samples. Furthermore, high correlations among proteins with high redundancy and moderate effects often lead to unstable selections and cause reproducibility issues. Ensemble feature selection in machine learning (ML) may identify a stable set of disease biomarkers that could improve the prediction performance of subsequent classification models and thereby simplify their interpretability. In this study, we developed a three-stage homogeneous ensemble feature selection (HEFS) approach for both identifying proteins and improving prediction accuracy. This approach was implemented and applied to ovarian cancer proteogenomics datasets comprising (1) binary putative homologous recombination deficiency (HRD)- positive or -negative samples; (2) multiple mRNA classes (differentiated, proliferative, immunoreactive, mesenchymal, and unknown samples). We conducted and compared various ML methods with HEFS including random forest (RF), support vector machine (SVM), and neural network (NN) for predicting both binary and multiple-class outcomes. The results indicated that the prediction accuracies varied for both binary and multiple-class classifications using various ML approaches with the proposed HEFS method. RF and NN provided better prediction accuracies than simple Naive Bayes or logistic models. For binary outcomes, with a sample size of 122 and nine selected prediction proteins using our proposed three-stage HEFS approach, the best ensemble ML (Treebag) achieved 83% accuracy, 85% sensitivity, and 81% specificity. For multiple (five)-class outcomes, the proposed HEFS-selected proteins combined with Principal Component Analysis (PCA) in NN resulted in prediction accuracies for multiple-class classifications ranging from 75% to 96% for each of the five classes. Despite the different prediction accuracies of the various models, HEFS identified consistent sets of proteins linked to the binary and multiple-class outcomes.

Intelligibility of Natively and Nonnatively Produced English Speech Presented in Noise to a Large Cohort of United States Service Members.

A corpus of English matrix sentences produced by 60 native and nonnative speakers of English was developed as part of a multinational coalition task group. This corpus was tested on a large cohort of U.S. Service members in order to examine the effects of talker nativeness, listener nativeness, masker type, and hearing sensitivity on speech recognition performance in this population. A total of 1,939 U.S. Service members (ages 18-68 years) completed this closed-set listening task, including 430 women and 110 nonnative English speakers. Stimuli were produced by native and nonnative speakers of English and were presented in speech-shaped noise and multitalker babble. Keyword recognition accuracy and response times were analyzed. General(ized) linear mixed-effects regression models found that, on the whole, speech recognition performance was lower for listeners who identified as nonnative speakers of English and when listening to speech produced by nonnative speakers of English. Talker and listener effects were more pronounced when listening in a babble masker than in a speech-shaped noise masker. Response times varied as a function of recognition score, with longest response times found for intermediate levels of performance. This study found additive effects of talker and listener nonnativeness when listening to speech in background noise. These effects were present in both accuracy and response time measures. No multiplicative effects of talker and listener language background were found. There was little evidence of a negative interaction between talker nonnativeness and hearing impairment, suggesting that these factors may have redundant effects on speech recognition. https://doi.org/10.23641/asha.26060191.

Profitability of Islamic Banks in Pakistan: An Empirical Analysis

The main object of this study is to investigate the Profitability of Islamic banks in Pakistan. The data duration of the study is 2006-2021 and penal regression analysis is used to test the Profitability of Islamic banks in the context of Pakistan. This study applied the Variance Inflation Factor (VIF), Breusch-Godfrey Serial Correlation LM and Breusch-Pagan-Godfrey tests to check the multicollinearity autocorrelation and heteroscedasticity respectively. According to the Hausman test, Redundant Effect Test is suitable for the current study. Results of the Random Effect Method indicate that the GDP and BS have statistically significant as well as positive effects on the Return on Assets (ROA). While the IR, NPL, and INF have statistically significant and negative effect on the Return on Assets (ROA). Results of the study suggest that factors that have a negative effect on the ROA, like interest rate, non-performing loan, and the inflation rate would be judgmentally investigated by the Islamic Bankers of Pakistan through structuring the bank’s policies. That would give support in the banks’ better performance and enhanced profitability, which would directly improve to their significant role in the economy.

Redundancy can hinder adult L2 grammar learning: evidence from case markers of varying salience levels.

Grammatical redundancy is a widespread feature across languages. Although redundant cues can be seen to increase the complexity and processing burden of structures, it has been suggested that they can assist language acquisition. Here, we explored if this learning benefit can be observed from the very initial stages of second language (L2) acquisition and whether the effect of redundancy is modulated by the perceptual salience of the redundant linguistic cues. Across two experiments, three groups of adult native speakers of English were incidentally exposed to three different artificial languages; one that had a fixed word order, Verb-Object-Subject, and two in which thematic role assignment was additionally determined by a low-salient (Experiment 1) or a high-salient (Experiment 2) redundant case marker. While all groups managed to learn the novel language, our results pointed towards a hindering role of redundancy, with participants in the non-redundant condition achieving greater learning outcomes compared to those in both redundant conditions. Results also revealed that this impeding effect of redundancy on L2 learners can be attenuated by the salience of the redundant cue (Experiment 2). In conjunction with earlier findings, the present results suggest that the effect of redundancy on L2 acquisition can be differentially manifested depending on the stage of L2 development, learners' first language biases and age.

Scheduling redundancy optimization for precast production to enhance disruption management in prefabricated construction

Redundancy is a highly effective approach for minimizing losses in precast production when faced with inevitable disruptions. However, existing studies have primarily focused on enhancing production redundancy in order to mitigate losses caused by disruptions, without considering the added production costs resulting from decreased efficiency. Besides, the cost-effectiveness of redundancy design may be influenced by the disruption types and their associated risk levels, which has not been thoroughly investigated. In this paper, a redundancy optimization model for precast production is proposed to achieve the trade-off between the redundancy benefits and the additional costs involved. The concept of production scheduling redundancy is firstly defined, and the benefits derived from its implementation are quantified. Additionally, different scenarios with high, moderate, and low occurrence levels of disruptions are designed to optimize the production redundancy in different situations. On this basis, the effectiveness and cost-benefits of redundancy are compared subject to various types and levels of disruptions. Finally, a case study is conducted to illustrate the model. The findings show that the machine breakdown is the most critical disruption in the precast production, and implementing redundancy measures prove to be more cost-effective in situations characterized by higher levels of risk. Besides, the optimal degree of redundancy is related to both the levels and the types of disruptions. The methodology of this paper can provide insights for disruption management in precast production and give full play to the benefits of prefabricated construction.